The present invention provides a target object elimination method based on a panoramic camera, the panoramic camera comprising at least two independent lenses, wherein the method comprises following steps: capturing one basic panoramic image by each of the independent lenses; recognizing a target object from each of the basic panoramic images; dividing each of the basic panoramic images into a plurality of image parts having a same or different size, wherein at least one of the image parts comprises the target object; deleting the one image part comprising the target object in each of the basic panoramic images; and combining all remaining image parts in each of the basic panoramic images to obtain a corrected panoramic image from which the target object is eliminated. By the present invention, the target object can be eliminated quickly and efficiently while ensuring the quality of the image.
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1. A target object elimination method based on a panoramic camera, the panoramic camera comprising at least two independent lenses, wherein the method comprises following steps: S 1 : capturing one panoramic image by each of the independent lenses; S 2 : recognizing a target object from each of the panoramic images; S 3 : dividing each of the panoramic images into a plurality of image parts having a same or different size, wherein at least one of the image parts comprises the target object; S 4 : deleting the one image part comprising the target object in each of the panoramic images; and S 5 : combining all remaining image parts in each of the panoramic images to obtain a corrected panoramic image from which the target object is eliminated; wherein, in the step S 5 , the combination of the image parts comprises following steps: S 51 : analyzing, based on an RGB gamut, a color value of each pixel in each of the image parts; and S 52 : judging whether the color value of each pixel in each of the image parts is the same; if yes, reserving the color value, and if no, averaging color values in all the image parts.
This invention relates to a method for eliminating unwanted objects from panoramic images captured by a panoramic camera system equipped with at least two independent lenses. The problem addressed is the presence of unwanted objects in panoramic images, which can disrupt the visual continuity or aesthetic quality of the captured scene. The method involves capturing multiple panoramic images simultaneously using the independent lenses. Each captured image is processed to identify and recognize a target object, which is then removed. The panoramic images are divided into multiple image parts, which may be of uniform or varying sizes, ensuring that at least one part contains the target object. The image part containing the target object is deleted from each panoramic image. The remaining image parts are then combined to reconstruct a corrected panoramic image without the target object. During the combination step, the method analyzes the color values of each pixel in the image parts using an RGB gamut. If the color values of corresponding pixels in different image parts are identical, they are retained. If the color values differ, the method averages the color values across all image parts to ensure a seamless and visually consistent result. This approach ensures that the final panoramic image is free of the target object while maintaining visual coherence.
2. The target object elimination method based on the panoramic camera according to claim 1 , wherein, in the step S 2 , the recognition of the target object from each of the panoramic images is realized by artificial recognition.
This invention relates to a method for eliminating target objects using a panoramic camera system. The method addresses the challenge of accurately detecting and removing unwanted objects from panoramic images, which is particularly useful in applications such as surveillance, autonomous navigation, and environmental monitoring where real-time object recognition is critical. The method involves capturing panoramic images using a panoramic camera, which provides a wide field of view. In a key step, the system recognizes target objects within each panoramic image using artificial recognition techniques, such as machine learning or computer vision algorithms. These techniques enable the system to identify and classify objects of interest, such as vehicles, pedestrians, or obstacles, with high accuracy. Once recognized, the target objects are eliminated from the panoramic images, either by masking, cropping, or other image processing methods, to produce a cleaned output. The artificial recognition step ensures that the system can adapt to various environments and object types, improving reliability and reducing false positives. The method may also include preprocessing steps to enhance image quality before recognition and post-processing to refine the elimination results. This approach enhances the usability of panoramic imaging systems by automating the detection and removal of unwanted objects, making it suitable for applications requiring real-time processing and high accuracy.
3. The target object elimination method based on the panoramic camera according to claim 2 , wherein the artificial recognition comprises following steps: S 211 : creating two longitudinal reference lines and two latitudinal reference lines on the panoramic image; S 212 : adjusting positions of the longitudinal reference lines and the latitudinal reference lines, so that the two latitudinal reference lines are respectively located above and below the target object and the two longitudinal reference lines are respectively located on two sides of the target object; S 213 : making a rectangular region by using four intersections of the two longitudinal reference lines and the two latitudinal reference lines as vertices; and S 214 : identifying the rectangular region as the target object, wherein the one image part comprising the target object in the step S 3 covers the rectangular region.
This invention relates to a method for eliminating target objects in panoramic images captured by a panoramic camera. The problem addressed is accurately identifying and isolating target objects within a panoramic image to facilitate their removal or analysis. The method involves artificial recognition of the target object through a series of steps. First, two longitudinal and two latitudinal reference lines are created on the panoramic image. These lines are then adjusted so that the latitudinal lines are positioned above and below the target object, while the longitudinal lines are placed on either side of the object. The intersections of these lines form a rectangular region, which is then identified as the target object. This rectangular region is subsequently used to define the area of the image that contains the target object, allowing for further processing such as elimination or analysis. The method ensures precise localization of the target object within the panoramic image, enabling accurate removal or manipulation of the object while preserving the surrounding image content.
4. The target object elimination method based on the panoramic camera according to claim 1 , wherein, in the step S 4 , each of the image parts is rectangular.
This invention relates to a target object elimination method using a panoramic camera, addressing the challenge of accurately identifying and removing unwanted objects from panoramic images. The method involves capturing a panoramic image, dividing it into multiple image parts, and analyzing these parts to detect and eliminate target objects. The key innovation is that each of the image parts is rectangular, ensuring consistent and efficient processing. The method begins by acquiring a panoramic image, which is then segmented into rectangular regions. Each region is analyzed to identify target objects based on predefined criteria, such as shape, color, or motion. Once detected, these objects are removed or masked out, resulting in a cleaned panoramic image. The rectangular division of the image ensures that the analysis is systematic and computationally efficient, reducing errors and improving accuracy. This approach is particularly useful in applications like surveillance, autonomous navigation, and augmented reality, where clear and unobstructed panoramic views are essential. The method leverages the panoramic camera's wide field of view to capture comprehensive scenes while ensuring that unwanted objects do not interfere with subsequent processing or analysis.
5. The target object elimination method based on the panoramic camera according to claim 1 , wherein, in the step S 1 , the target object is located in front of the independent lens whenever the panoramic image is captured.
This invention relates to a method for eliminating target objects in panoramic images captured by a panoramic camera system. The method addresses the problem of unwanted objects appearing in panoramic images, particularly when the camera is mounted in a fixed position and captures a wide field of view. The invention ensures that a target object, such as a camera housing or mounting structure, is not visible in the final panoramic image by positioning the object in front of an independent lens during image capture. The panoramic camera system includes multiple lenses arranged to capture overlapping images, which are then stitched together to form a seamless panoramic view. The method involves a step where the target object is deliberately placed in front of one or more lenses to prevent it from appearing in the final stitched image. By ensuring the object is always in front of the lens during capture, the system avoids including it in the panoramic output. This approach improves image quality by eliminating unwanted obstructions while maintaining the full field of view. The method is particularly useful in applications where the camera is mounted in a fixed position, such as in surveillance, automotive, or virtual reality systems, where minimizing visual obstructions is critical. The technique leverages the overlapping nature of panoramic imaging to ensure seamless integration of captured images while excluding the target object from the final output.
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September 4, 2019
February 1, 2022
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